Broad Research Interests: Wavelets, Sparse Optimization Theory and Inverse Problems

Sparse optimization theory (popularly known as Compressive Sensing) is an interface area between Algebra and Optimization, which aims at providing some classes of linear systems with sparse (or economical) descriptions. Applications of this research area are far and wide in diverse fields including medical imaging.

My current research interests lie in Finite frames, Sparsity-seeking optimization techniques and their applications involving Data-driven learning methods and Inverse problems. My previous research, nevertheless, was directed toward Wavelets, Reconstruction in Tomography.